Kisung Nam
Short Bio
Kisung Nam is a Ph.D. candidate at the Graduate School of Data Science in Seoul National University. He is a member of Lee Lab for Statistical Genetics and Data Science led by his advisor Dr. Seunggeun (Shawn) Lee. His current research interest includes (but not limited to) statistical methods, modeling, data analysis for genetic and finance datasets.
Before joining Lee Lab, he worked as a senior manager at Financial Supervisory Service (FSS) of Korea. He also has extensive experience in financial data analysis and laws, especially about the asset management industry and derivative markets. He received M.S. in Management Engineering (Finance track) under supervision of Dr. Hoe Kyung Lee and Dr. Tong Suk Kim and B.S. in Mathematical Sciences, both from Korea Advanced Institute of Science and Technology (KAIST).
Please refer to my CV for more details.
Education
Ph.D. Candidate in Data Science, Seoul National University (Mar 2020 - Aug 2025(exp.))
M.S. in Management Engineering (Finance track), KAIST (Feb 2012 - Feb 2014)
B.S. in Mathematical Sciences (Summa Cum Laude), KAIST (Mar 2006 - Feb 2012)
Experience
Visiting Research Scholar, Department of Biostatistics, University of Michigan (Sep 2023 - Feb 2024)
Mentor: Dr. Bhramar Mukherjee
Senior Manager, Financial Supervisory Service (FSS) of Korea (2014 - present, currently on a leave since March 2020)
Internship, Samsung Asset Management (Jun 2013 - Aug 2013)
Internship, Korea Hydro and Nuclear Power (Jun 2008 - Aug 2008)
J. Flanagan, K. Nam, S. Lee. ENCODE guided WGS analysis can identify trait-associated regulatory regions driven by rare variants, medRxiv, 2024. [Link]
E. Park*, K. Nam*, S. Jeong*, ..., S. Lee. Meta-SAIGE: Scalable and accurate meta-analysis for rare variants, medRxiv, 2024. [Link]
K. Nam, ..., S. Lee. Rare variant effect estimation and polygenic risk prediction, medRxiv, 2024. [Link]
P. Nagarajan, ..., K. Nam, ..., H. Wang. A large-scale genome-wide study of gene-sleep duration interactions for blood pressure in 811,405 individuals from diverse populations, medRxiv, 2024. [Link]
L. Fritsche, K. Nam, ..., B. Mukherjee. Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks, PLOS Genetics, 2023. [Link]
A. Campos, ..., K. Nam, ..., L. Yengo. Boosting the power of GWAS within and across ancestries using polygenic scores, Nature Genetics, 2023. [Link]
J. Kim, J. Lee, K. Nam, S. Lee. Investigation of genetic variants and causal biomarkers associated with brain aging, Scientific Reports, 2023. [Link]
M. Kanai, ..., K. Nam, ..., H. Finucane. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution, Cell Genomics, 2022. [Link]
W. Zhou, ..., K. Nam, ..., B. Neale. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease, Cell Genomics, 2022. [Link]
K. Nam, J. Kim, S. Lee. Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits, Cell Genomics, 2022. [Link]
Y. Zhuang, B. Wolford, K. Nam, ..., S. Lee. Incorporating family disease history and controlling case–control imbalance for population-based genetic association studies, Bioinformatics, 2022. [Link]
K. Park, ..., K. Nam, ..., W. Li. Real-time mask detection on Google edge TPU, arXiv, 2020. [Link]
Grants and Awards
Research Grants for Ph.D. Candidates, National Research Foundation (2023 - 2025)
Youlchon AI Young Researcher Scholarship, Youlchon Foundation (2023)
Reviewer's Choice Award in 2022 ASHG Annual Meeting, American Society of Human Genetics (2022)
Governor Award, Financial Supervisory Service (2019)
Social Science Scholarship, Korea Student Aid Foundation (2013 - 2014)
Institutional Scholarship, KAIST College of Business (2012 - 2014)
Graduation Summa Cum Laude, KAIST (2012)
Science and Engineering Scholarship, Korea Student Aid Foundation (2006 - 2012)
Prize for Encouragement, Samsung Human-Tech Thesis Prize (2005)
Teaching & Talks
Invited Lecture, Korea Hydro & Nuclear Power Radiaton Health Institute (May 2024 - Oct 2024)
Invited Talk, Seoul National University Bundang Hospital (Jul 2023, Aug 2023)
Teaching Assistant, Computing 1 for Data Science, Seoul National University (Fall 2022)
Teaching Assistant, Genomics and Clinical Data Analysis, Seoul National University (Spring 2022, Spring 2023, Fall 2024)
Teaching Assistant, Advanced Statistical Analysis, Seoul National University (Fall 2021)
Guest Lecturer, Financial Institutions (금융기관경영론), Myongji University (Fall 2021)
Teaching Assistant, Probability and Statistics for Data Science Bootcamp, Seoul National University (Jan 2021)
Mentor, Tutorial lecture on biobank data analysis for new Lee Lab members (2021, 2022, 2023)
Contact
E-mail: kisung.nam [at] snu.ac.kr